期刊
STATISTICS IN MEDICINE
卷 38, 期 8, 页码 1484-1501出版社
WILEY
DOI: 10.1002/sim.8078
关键词
probabilistic index; proportional hazard model; proportional odds model; semiparametric regression
类别
资金
- Research Fund Flanders (FWO) [V403114N, K211116N, G020214N]
Semiparametric linear transformation models form a versatile class of regression models with the Cox proportional hazards model being the most well-known member. These models are well studied for right censored outcomes and are typically used in survival analysis. We consider transformation models as a tool for situations with uncensored continuous outcomes where linear regression is not appropriate. We introduce the probabilistic index as a uniform effect measure for the class of transformation models. We discuss and compare three estimators using a working Cox regression model: the partial likelihood estimator, an estimator based on binary generalized linear models and one based on probabilistic index model estimating equations. The latter has a superior performance in terms of bias and variance when the working model is misspecified. For the purpose of illustration, we analyze data that were collected at an urban alcohol and drug detoxification unit.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据